Recent days, research in wireless network becomes major area for the past few decades. In wireless routing many routing methods such as table driven, source driven; many characteristics such as reactive routing, proactive routing; many routing algorithms such as dijikstra’s shortest path, distributed bell-man ford algorithm are proposed in the literature. For effective wireless routing, the rec...

We present two heuristic mesh-partitioning methods, both of which build on the multiple ant-colony algorithm in order to improve the quality of the mesh partitions. The first method augments the multiple ant-colony algorithm with a multilevel paradigm, whereas the second uses the multiple ant-colony algorithm as a refinement to the initial partition obtained by vector quantization. The two meth...

This paper introduces the basic theory and procedure for working out solutions of ant colony genetic algorithm, describes optimization, constraints and objectives of construction project scheduling, then establishes basic model for scheduling optimization of construction project, and put forward improved ant colony genetic algorithm for solving the basic model. Performance of ant colony genetic...

Community assembly is driven by multiple factors, including resource availability and habitat requirements. Litter nesting ants respond to food and nest site availability, and adding food and nests may increase ant species richness and abundance. However, litter decomposers share food resources with ants, and increasing food availability may speed decomposition processes, eliminating twigs and ...

the one-dimensional cutting stock problem, has so many applications in lots of industrial processes and during the past few years has attracted so many researchers’ attention all over the world. in this paper a meta-heuristic method based on aco is presented to solve this problem. in this algorithm, based on designed probabilistic laws, artificial ants do select various cuts and then select the...

this paper considers identical parallel machines scheduling problem with past-sequence-dependent setup times, deteriorating jobs and learning effects, in which the actual processing time of a job on each machine is given as a function of the processing times of the jobs already processed and its scheduled position on the corresponding machine. in addition, the setup time of a job on each machin...

Ant Colony Optimization (ACO) algorithm is a novel metaheuristic algorithm that has been widely used for different combinational optimization problem and inspired by the foraging behavior of real ant colonies. Ant Colony Optimization has strong robustness and easy to combine with other methods in optimization. In this paper, an efficient ant colony optimization algorithm with uniform mutation o...

Ant colony algorithms are a class of metaheuristics which are inspired from the behaviour of real ants. The original idea consisted in simulating the stigmergic communication, therefore these algorithms are considered as a form of adaptive memory programming. A new formalization was proposed for the design of ant colony algorithms, introducing the biological notions of heterarchy and communicat...

An algorithm for edge detection with low contrast image using improved ant colony optimization is proposed in this paper. In edge detection, some parts of the edge are disappeared or disconnected because of low contrast in their intensities. This paper concentrates to this low-contrast problem. To detect these pixels, the direction tendency of edge lines is computed and ant colony optimization ...

In this paper, we present an improved continuous ant colony algorithm for global optimization of continuous functions. We show how to improve the quality of Ant Colony Optimization, ACO, to solve continuous optimization problems. We present the general idea, implementation, the analysis of its convergence and results obtained. We compare the results with Adaptive Genetic Algorithm, AGA, and Con...